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Price-per-square-foot is a poor way of guessing the value of a typical home. If you are not familiar with this method, the way it is supposed to work is you take a group of homes that have recently sold in the neighborhood, add all the sales prices together, then add all the square footages together, and divide the two to get average price-per-square-foot (PPSF). Then supposedly you can compare that PPSF with the PPSF of a home in which you are interested. On top of being a flawed method for single family homes, it’s usually poorly implemented by users who only use one home to derive the number, rather than a group. And usually it is not the most representative home when compared to the house of interest. For example, Sellers will often use the highest selling home in the neighborhood for comparison to their home, though the highest selling home is usually much more improved. Buyers on the other hand will often choose a lower priced home in the neighborhood for comparison, even though it's not a house they would be interested in buying.
The problem with price-per-square-foot, is that it estimates the value of a house heavily on its square footage. Buyers don’t really know the square footage of a home just by looking at it. They get a feel for the home by visiting it and decide whether they like it or not based on look, the flow, and condition. You can have more square footage in a home but have it feel less livable than a smaller well laid out home. Another problem with PPSF is in the way that it is used. As commonly used, it includes the cost of the land, the curb appeal, the condition, the cost of upgrades, the layout, etc., which are not related to interior square footage. Another home that has more or less square footage doesn’t necessarily need its lot value adjusted, or the updates adjusted, which is what is implied when you apply this method. In some cases the lot value can be much more than the house value, to the point where the house square footage is inconsequential. So using this method could result in the user making $150 adjustments for each additional square foot, where realistically the adjustment should be $25 or less. An error that is six times more than justified.
Perhaps the best way to demonstrate how problematic PPSF is, would be to test it on a group of similar homes for which you know the actual sales price. For example, a group of similar homes, in a newer neighborhood, that sold about the same time. Once the average PPSF is calculated using the sales prices and the square footage amounts, we can simply take that number and multiply it back by each individual home’s square footage and see how close we get to calculating the known sales price. It should be realized that some variation can be expected when choosing comparable homes, because you seldom have enough recent “Solds” in a neighborhood to find exact matches in terms of size, number of bedrooms, number of bathrooms, basement finishes, and number of garage bays, but often you can get close. Condition is probably a bigger factor most of the time. In this demo we’ll cheat a little just to prove a point and choose a new production neighborhood where there are several similar homes that sold in the same year and are obviously in the same new condition.
For the demo, homes were selected with 5 bedrooms, 3 baths, 3 car garages, with unfinished basements, and on similar lots. Below are the results. The neighborhood selected was Westmont Estates in Carmel. The homes all sold new and sold for the exact same price as they were listed; with no price reductions. In the table below you will find the sales price, the average PPSF of the group, the Estimated Sales Price when reapplying the PPSF, and the PPSF error, which is the difference between the predicted sales price using PPSF and the actual known sales price. The average PPSF of the group was $82.28 and it was calculated by taking the sum of the Sales Prices of the group of homes ($2,228,068) and dividing it by the sum of the total square footage (27079 sqft). Note that I used total square footage rather than Main and Upper Square Footage. Fannie Mae Guidelines exclude basement square footage from the reported square footage. Most Realtors do not include basement in their reported square footage, but instead report basement square footage seperately. You will get similar errors if you use Main and Upper square footage, except when comparing homes with nicely finished basements. Then you get bigger errors. Most Buyers and Sellers are using the square footage posted by online sites like Zillow or Realtor.com, which both include the basement in the square footage. So it is safe to assume that this is the way most people are using PPSF.
|MLS Number||Sales Price||SqFt Main/Upper||SqFt Total||Est Price||Error|
|Total SP:||$2,228,068||Total SF:||27079|
So by looking at the results in Table 1, specifically the error column, the error when using the PPSF method for estimating the sales price of this particular group of homes ranges from overestimating the sales price by $47,435 on top home to underestimating the sales price on the bottom home by $54,920. That is a spread of over $100,000 on an average priced home of $446,000. That is a huge error range. In fact in this particular example, you would be sigificantly more accurate if you simply used the Average Sales Price. As a Buyer of a $445K home, would you feel comfortable that you might be paying $50K too much, or as a Seller would you feel comfortable knowing you might be selling at $50K below market price? That is what might happen if this method is how you price homes.
The right answer is to price your home using a more involved standard similar to how an appraisal is done. Most of your experienced Realtors know how to do a Competitive Market Analysis or CMA. There is a quick CMA available to Realtors and Appraisers, which is the PPSF estimator, but that tool is better suited for commercial space or condominiums and not your typical residential home. The popular TV flipping shows, and some big box builders like to use PPSF when if fits to their agenda, so the term has permeated the industry making it seem like it is credible. An actual CMA is around 70 pages in length and involves picking comparable homes, reviewing each home in depth, normalizing the homes by adjusting for number of bedrooms, fireplaces, updates, curb appeal, etc., as well as square footage.
Much of the adjustment in a CMA involves some Realtor insight to what current Buyers are thinking in terms of deductions. A Realtor, who takes the time to do a CMA, is better negotiator and defender of your price, because they know how your home really stacks up. We have only had a few appraisal issues in our career, but because we understood the process and knew exactly how the appraisers should value homes, we were able to get every one of those overturned, which is a rare feat.
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